一种基于遗传蚁群算法的海量案例检索方法

Based on The Genetic ant Colony Algorithm for Case Retrieval Method

针对传统的蚁群算法在海量案例检索应用中,由于冗余案例数据的干扰,算法易陷入局部最优解而不能对解空间进行全面搜索的缺陷,将具有快速良好的全局搜索能力的遗传算法加入到蚁群系统的每一次迭代过程中,提出了一种融合遗传算法和蚁群算法的案例检索算法,对案例进行聚类处理,建立案例映射模型,克服了蚁群算法的缺陷。实验结果表明,利用本文提出的遗传蚁群算法进行案例检索,能够有效地提高案例检索的效率,取得了令人满意的效果。

Research to improve the case retrieval efficiency problem.Ant colony algorithm is easy to fall into the local optimal solution and not to the solution space for comprehensive search of the defect,will have fast good global search ability of genetic algorithm to join to the ant colony system of each iteration process,put forward a kind of genetic algorithm and fusion of ant colony algorithm case retrieval algorithm,overcome the defects of ant colony algorithm.The case of the clustering processing, build case mapping model.The experimental results show that,using the proposed genetic ant colony algorithm case retrieval, can effectively improve the efficiency of the case retrieval satisfactory results have been obtained.